| Under the prevailing Intelligent Transportation System functional specifications, real-time vehicle route guidance is one of the important capabilities offered by Advanced Traveler Management and Information Systems (ATMIS) for on-line traffic management to improve the performance of congested networks. The route guidance information, which aims at coordinating drivers by assigning them to a set of paths connecting their origins and destinations, is usually obtained by solving some variant of the Dynamic Traffic Assignment (DTA) problem.; Considered as critical issues in the ATMIS architecture. DTA problems have been extensively studied in the last decade. Researchers have proposed various DTA problem classes and formulations, and have gained basic understanding of the solution characteristics. Although a vast amount of intellectual effort has been invested in characterizing and solving DTA problems, the current state-of-the-art falls short of providing DTA solutions that are guaranteed to be effective and robust in real-world operation. The present research is motivated by the need for a DTA framework that offers significant potential for successful real-world operation. The objective of this dissertation is to develop a generalized DTA framework that combines the advantages of both centralized and decentralized paradigms and circumvents the respective disadvantages, so as to provide efficient and robust dynamic traffic assignment solutions under various network conditions.; To achieve the generalization of the DTA framework, this dissertation presents a Hybrid DTA (HDTA) framework. The HDTA approach envisions a hierarchical routing decision process achieved through the careful interplay between a Centralized DTA model (CDTA) and a Decentralized DTA (DDTA) capability. The CDTA model supplies anticipatory a priori routing decisions, while the DDTA model generates locally optimized solutions online.; To further improve online operation performance and robustness of the HDTA, an Online Routing Profile Updating Automata (ORPUA) model is proposed. The ORPUA dynamically adjusts the routing profile based on the online performance competitiveness measure of CDTA and DDTA-guided vehicles. It allows HDTA to adaptively and robustly maintain its online operating performance vis-à-vis general demand or supply scenarios. Numerical experiments demonstrate the effectiveness of ORPUA under the scenarios in which CDTA's inputs are of varying accuracy levels. |
